1. Field of the Invention
The present invention relates to a method for segmentation of a structure, more particularly segmentation of a vessel structure in a 3D medical image reconstruction.
2. Description of the Related Art
3D reconstructions of MRA (magnetic resonance angiography) and CTA (X-ray CT angiography), in which vessels are enhanced to have higher intensity values, are widely used for the diagnosis of serious circulation diseases.
In such studies, the segmentation of vascular structures is particularly valuable for diagnosis assistance, treatment and surgery planning. Indeed, it is a fundamental step for the accurate visualization of vessels from complex datasets and for the quantification of pathologies.
It is also a valuable input for advanced vessel tracking applications.
Vascular segmentation is an especially specific and challenging problem. Besides acquisition-dependent considerations about contrast, resolution, noise and artifacts, vascular networks can be particularly complex structures. Blood vessels potentially exhibit high variability of size and curvature. Their appearance and geometry can be perturbed by stents, calcifications, aneurysms, and stenoses. Furthermore, they are often embedded in complex anatomical scenes, surrounded by other organs, mainly bones which have a similar density, in an angiographic setting.
In addition to the above general considerations, more specific image properties, such as the pixel intensity variations related to the local amount of blood flow and the partial volume effects, make the vessel segmentation a difficult task. The partial volume effects mainly affect thin vessels reducing the intensity of vessel parts as the low pass filtering effect. So the range of the intensity of the blood vessel is not restricted in a small interval but spread widely.
For all these reasons, the generic region growing, as well as thresholding, is not appropriate to extract the whole part of the vessels: it usually results in false detection problems. To get correct segmentation results by region growing, it is necessary to rely on flexibly adapted approaches according to the local characteristics in each region.
Similar problems may be encountered when segmenting other structures such as bone structures.
It is an aspect of the present invention to provide a segmentation method that overcomes the described disadvantages of prior art methods.